Systems and methods to determine a location of a mobile device

ABSTRACT

Systems and methods to determine a location of a mobile device by combining a radio frequency navigation system and an inertial navigation system, where the radio frequency navigation system determines a location of the mobile device in reference to a map of radio frequency signals and the inertial navigation system based on dead reckoning the position of the mobile device based on measurements from motion sensors and/or magnetic field sensors. The mobile device combines the position determination results from the radio frequency navigation system and the inertial navigation system to determine two successive locations. A heading of the user of the mobile device is computed from the two successive locations without using the orientation of the mobile device.

RELATED APPLICATIONS

The present application claims the benefit of the filing dates of Prov.U.S. Pat. App. Ser. No. 62/408,265, filed Oct. 14, 2016 and entitled“Systems and Methods to Determine a Location of a Mobile Device”, Prov.U.S. Pat. App. Ser. No. 62/408,261, filed Oct. 14, 2016 and entitled“Systems and Methods to Determine a Location of a Mobile Device”, andProv. U.S. Pat. App. Ser. No. 62/408,264, filed Oct. 14, 2016 andentitled “Systems and Methods to Determine a Location of a MobileDevice”, the entire disclosures of which applications are herebyincorporated herein by reference.

The present application relates to U.S. patent application Ser. No.15/193,377, filed Jun. 27, 2016, which claims the benefit of the filingdates of: Prov. U.S. Pat. App. Ser. No. 62/190,690, filed Jul. 9, 2015,and Prov. U.S. Pat. App. Ser. No. 62/192,795, filed Jul. 15, 2015, theentire disclosures of which applications are hereby incorporated hereinby reference.

FIELD OF THE TECHNOLOGY

At least some embodiments of the present disclosure relate to positiondetermination systems in general and more particularly but not limitedto the determination of a position of a mobile device using beacondevices that transmit wireless signals.

BACKGROUND

U.S. Pat. No. 8,179,816 discloses an indoor positioning system using anarrowband radio frequency transceiver and discussed a number of otherindoor positioning systems. For example, some systems usepower-of-arrival (PoA) from a set access points in accordance with IEEE802.11 for wireless local area networks to determine the location of amobile device. For example, some systems use Time-of-flight (ToF) ofsignals from or to satellites or base-stations to convert the arrivaltime to distances in view of the propagation speed of signals.

U.S. Pat. App. Pub. No. 2012/0226467 discloses an inertial navigationunit that utilizes multiple accelerometers to gather specific force datafor improvement of the initialization, navigation, assistance, orcorrective processes.

U.S. Pat. App. Pub. No. 2002/0198656 discloses an Inertial GPSnavigation system that has a GPS sub-system and an inertial sub-system.If the receiver loses GPS satellite signals, the receiver utilizes theinertial position, velocity and covariance information to speed up GPSsatellite signal re-acquisition and associated ambiguity resolutionoperations.

U.S. Pat. App. Pub. No. 2012/0173139 discloses the use of magneticfingerprint of locations to estimate the position of a navigationdevice.

The disclosures of the above discussed patent documents are herebyincorporated herein by reference.

BRIEF DESCRIPTION OF THE DRAWINGS

The embodiments are illustrated by way of example and not limitation inthe figures of the accompanying drawings in which like referencesindicate similar elements.

FIG. 1 shows a system configured to determine a position of a mobiledevice in an indoor environment according to one embodiment.

FIG. 2 shows a mobile device for its location determination according toone embodiment.

FIG. 3 shows a method to determine a location of a mobile deviceaccording to one embodiment.

FIG. 4 illustrates a data processing system according to one embodiment.

FIG. 5 shows a mobile device for its location determination according toone embodiment.

FIG. 6 shows a method to improve an inertial position determinationsystem based on a radio frequency position determination systemaccording to one embodiment.

FIG. 7 shows a method to combine an inertial position determinationsystem and a radio frequency position determination system according toone embodiment.

FIG. 8 shows a method to improve a radio frequency positiondetermination system based on an inertial position determination systemaccording to one embodiment.

FIG. 9 shows a method to combine the location determination results froman inertial position determination system and a radio frequency positiondetermination system according to one embodiment.

FIG. 10 shows a method to filter the location determination results froma radio frequency position determination system based on a minimumdistance according to one embodiment.

FIG. 11 shows a method to filter the location determination results froma radio frequency position determination system based on a maximumdistance according to one embodiment.

FIG. 12 shows a method to determine the heading of a person carrying amobile device according to one embodiment.

DETAILED DESCRIPTION

The following description and drawings are illustrative and are not tobe construed as limiting. Numerous specific details are described toprovide a thorough understanding. However, in certain instances, wellknown or conventional details are not described in order to avoidobscuring the description. References to one or an embodiment in thepresent disclosure are not necessarily references to the sameembodiment; and, such references mean at least one.

In one embodiment, a system is configured to provide improved positiondetermination results by distributing beacon devices at pedestriantraffic “choke points”, such as door entrances, elevator entrances andtops and bottoms of escalators, to obtain a very precise position of themobile device based on the radio frequency power measurement of thebeacon devices positioned at these choke points. The results can be usedto correct the positions of the mobile device determined using othertechnologies, such as providing an initial position to be used by aninertial navigation system to track the location of the mobile device,correcting the drift in the tracked location provided by the inertialnavigation system, imprecision of Wi-Fi and beacon fingerprinting,and/or providing a much more accurate and robust positioning method.

FIG. 1 shows a system configured to determine a position of a mobiledevice in an indoor environment according to one embodiment. Forexample, the system of FIG. 1 can be used to improve positiondetermination results by distributing beacon devices at pedestriantraffic “choke points” as discussed above.

In FIG. 1, the position of the mobile device (101) in a multi-floorindoor environment is determined and/or tracked via the use of beacons(103 and 105) disposed at selected locations of a transport corridor(109), such as the top and bottom of an escalator or a stairway, theentrances of an elevator connecting between the floors (111 and 113),etc.

In FIG. 1, the direction of the location of one beacon B (103) to thelocation of another beacon A (105) corresponds to the direction oftraffic flow on the corridor (109). The transport corridor (109)substantially confines the possible locations of the mobile device (101)on one or more predefined line segments identified by the locations ofthe beacons (103, 105), if the mobile device (101) is determined to bein the traffic on the corridor (109). Thus, detecting the mobile device(101) being in the traffic simplifies the position determination of themobile device (101) and improves the accuracy of the determinedposition.

In FIG. 1, the mobile device (101) is configured to receive signals fromthe beacons (103 and 105) and monitor the signal strength of thereceived beacon signals. When the mobile device (101) moves past abeacon (e.g., 105), the strength of the signal received from the beacon(105) reaches a peak and then drops off from the peak. The time instanceat which the beacon signal reaches the peak corresponds to the momentwhere the mobile device (101) is the closest to the location of thebeacon (105).

In general, the mobile device (101) may move close to the beacon (105)and then move away from the beacon (105), causing the mobile device(101) to detect a peak in beacon signal, without actually moving to thelocation of the beacon (105).

When the mobile device (101) detects that a peak in signal strength fromthe beacon A (105) and then a peak in signal strength from the beacon B(103), the mobile device (101) determines that the movement of themobile device (101) is consistent with the traffic flow in the transportcorridor (109).

Furthermore, the time gap between the peak in signal strength from thebeacon A (105) and the peak in signal strength from the beacon B (103)is determined to be the travel time from the vicinity of beacon A (105)to the vicinity of beacon B (103). The time gap can be compared with thetime gap of expected traffic flowing through the transport corridor(109). If the time gaps match with each other, the determination of themobile device (101) moving along the corridor (109) during the timeperiod between the signal peaks can be confirmed. Thus, a location ofthe mobile device determined using another location determination systemcan be corrected and/or improved based on the timing of the mobiledevice traveling in the traffic flow; alternatively or in combination,the position of the mobile device determined in connection with thetraffic flow can be used as an initial position of the mobile device insubsequent tracking of the position of the mobile device.

For example, when the corridor (109) is an escalator, the expectedtraffic flow can be determined based on the speed of the escalator. Forexample, when the corridor (109) is an elevator, the expected trafficflow can be determined from the speed of the elevator. For example, whenthe corridor (109) is a stairway, an average traffic flow speed can bemeasured for the stairway to determine a typical time gap for travelingfrom the vicinity of the beacon A (105) to the vicinity of the beacon B(103).

When the time gap between the peak in signal strength from the beacon A(105) and the peak in signal strength from the beacon B (103) isconsistent with the expected traffic flowing through the transportcorridor (109), the mobile device (101) is determined to have traveledbetween the locations of the beacon A (105) and the beacon B (103).Thus, the travel speed and position of the mobile device (101) duringthe time period between the peaks in beacon signal strength aredetermined in relation with the known path of the corridor (109) withgreat precision.

The determined position and the travel speed of the mobile device basedon the beacons in connection with the information of the traffic flowcan be used to augment the performance of other indoor positioningsystems.

For example, in one embodiment, the mobile device (101) further includesan inertial guidance system that uses motion sensors, such asaccelerometers and gyroscopes, to calculate, via dead reckoning, theposition, orientation, and velocity (including the direction and speedof movement) of the mobile device (101). For example, the accelerationover a period of time provides the change in the speed of the mobiledevice (101); and the speed of the mobile device (101) over a period oftime provides the change in the position of the mobile device (101).

The determined position and travel speed of the mobile device (101) onthe corridor (109) can be used to provide an initial position and/or thespeed for the inertial guidance system to determine, using themeasurements from the motion sensors, the subsequent location and spendof the mobile device (101) after the mobile device moves away from thecorridor (109).

For example, when the mobile device (101) moves to the next corridor(109), or travels back via the corridor (109), the determined positionand travel speed of the mobile device (101) in the corridor (109) can beused to reset the position and/or the speed of the mobile device (101)for subsequent location tracking via the inertial guidance system. Thus,each time the mobile device (101) moves through a corridor (109) withthe correspondingly equipped beacon sets (103 and 105), the mobiledevice (101) can reinitialize the inertial guidance system to correctdrift in the results provided by the inertial guidance system.

When the corridor (109) is an elevator, a signal beacon (105) may beinstalled inside the elevator. When the mobile device (101) enters theelevator, the beacon signal strength reaches a highest level and stay atthe level during the time period of the elevator traveling from onefloor (113) to another floor (111). When the mobile device leaves theelevator, the beacon signal strength drops off from the highest level.Thus, from correlating the timing of the beacon signal strength reachingthe highest level and dropping off from the highest level with the timeof the travel of the elevator, the speed and position of the mobiledevice (101) within the elevator can be determined with great accuracy.The floor position of the elevator can be used to accurately identifythe position of the elevator. Optionally, the beacon signal may includethe data reporting the floor position of the elevator and/or locationcoordinates of the beacon, which data can be used in the mobile device(101) to determine the location and travel speed of the mobile device(101) for the time period in the elevator. Alternatively, multiplebeacons (105, 103) can be placed at the exit locations of the elevatorin a way similar to beacons being placed on or near an escalator orstairway to provide the beacon location and/or identity information.

The mobile device (101) may optionally include a radio frequencyfingerprint-based location determination system. When the mobile device(101) has a radio frequency fingerprint-based location determinationsystem, the beacon signals can be used to improve the locationdetermination results of the radio frequency fingerprint-based locationdetermination system. For example, a distribution of radio frequencyfingerprints of the indoor environment can be obtained via a surveyoperation. Different locations inside the multi-floor environmentgenerally have different radio frequency fingerprints and differentrelations with neighboring locations. Thus, when the mobile device (101)moves around the environment and measures the radio frequencyfingerprints, the measured radio frequency fingerprints can becorrelated with the predetermined distribution of radio frequencyfingerprints to determine a location of the mobile device (101).

However, in certain environments, different floors may have similardistribution of radio frequency fingerprints. Thus, the radio frequencyfingerprint-based location determination system may have difficulties indetermine accurately the floor on which the mobile device (101) iscurrently located. The determination of the mobile device (101) movingthrough the corridor (109) provides the accurate information about thefloor on which the mobile device (101) is currently located and thus,allows the radio frequency fingerprint-based location determinationsystem to correlate the measured radio frequency fingerprints with thedistribution of the correct floor to provide accurate results withreduced correlation time.

When the mobile device (101) is equipped with multiple positioningsystems, the mobile device (101) is configured to combine the resultsfrom the multiple positioning systems to provide an improved overallestimate of the position of the mobile device (101).

For example, when the mobile device (101) travels through the corridor(109), the accurate position and speed of the mobile device (101) can beused to provide the initial position and speed of the mobile device(101) for the inertial guidance system that uses the measurement of themotion sensors to updated the subsequent location and speed of themobile device (101). After a period of time, the drift in the inertialguidance system may lead to increased errors in the determined locationand speed of the mobile device (101). Thus, after a threshold period oftime, if the inertial guidance system cannot be reset via thepositioning results from traveling through a corridor equipped with thebeacons (103, 105), the mobile device (101) may use the location resultsfrom the radio frequency fingerprint-based location determinationsystem.

The accuracy of the results from the radio frequency fingerprint-basedlocation determination system are associated with the locationscalculated by matching the measured radio frequency fingerprints withthe predetermined distribution of radio frequency fingerprints; and theaccuracy of the results from the inertial guidance system are determinedfrom the lapsed time from the initialization using an accurate resultfrom the beacons (103, 105) installed near the corridor (109). Themobile device (101) combines the results from the radio frequencyfingerprint-based location determination system and the inertialguidance system based on the accuracy estimates of the respectiveresults. For example, when the result of the radio frequencyfingerprint-based location determination system is more than a thresholdbetter than the result of the inertial guidance system, the result fromthe inertial guidance system is discarded; when the result of the radiofrequency fingerprint-based location determination system is more than athreshold worse than the result of the inertial guidance system, theresult from the radio frequency fingerprint-based location determinationsystem is discarded; and otherwise, the result of the radio frequencyfingerprint-based location determination system and the result of theinertial guidance system are combined (e.g., via an weighted average,where the weights for the results from the different systems areproportional to the estimated accuracy of the respective results).

The mobile device (101) (or a remote server in communication with themobile device (101)) is configured to remove and/or reduce the flaws ofthe individual measuring system (e.g., the inertial guidance system, theradio frequency fingerprint-based location determination system, and thechoke-point-beacon-based system) by examining in real time the data ofeach individual system, using the known propensity of the types oferrors that one system produces and the real time data produced byanother system to eliminate the types of errors.

As an example, a radio frequency fingerprint-based locationdetermination system has the propensity to report jumps in the positionof the mobile device. The person may or may not be actually turning tothe jump location. An inertial system does not report positions withthis type of positioning errors. Therefore, when a jump signature isrecognized in the reported positioning results of a radio frequencyfingerprint-based location determination system, a solution integrationengine, implemented in the mobile device (101) or a remote server incommunication with the mobile device (101), is configured to eliminatethe faulty position provided by the radio frequency fingerprint-basedlocation determination system and utilizing the position determined bythe inertial guidance system.

A typical inertial guidance system has a tendency to drift, which isrecognized by the solution integration engine. Once a series of highquality positions has been received which have not had any recognizederror artifact and the inertial system is exhibiting its drift tendencyaway from those high quality positions determined by the radio frequencyfingerprint-based location determination system, the inertial system canbe reset/initialized according to the positions determined by the radiofrequency fingerprint-based location determination system, and/orcreating a composite heading figure using the data from both systems.

Thus, the present disclosure provides a plurality of position correctiontechniques and system calibration techniques based on the known errorsignatures and tendencies of individual positioning systems used by themobile device (or a remote server) and/or beacon signals associated withknown locations and known traffic speed.

FIG. 2 shows a mobile device for its location determination according toone embodiment. For example, the mobile device (101) of FIG. 2 can beused in the system of FIG. 1. In FIG. 2, the mobile device (101)includes one or more transceivers (123) to receive signals from thebeacons (103, 105) to detect the peaks of their signals corresponding tothe travel of the mobile device (101) between the locations of thebeacons.

Optionally, one or more transceivers (123) are further used tocommunicate with the Wi-Fi access points (e.g., 107) in the environmentto support radio frequency fingerprint-based location estimation.

In FIG. 2, the mobile device (101) further includes motion sensors(121), such as accelerometers and gyroscopes to support inertialguidance based location estimation.

The mobile device (101) includes memory (167) storing a mobileapplication (125) having instructions configured to instruct one or moremicroprocessor(s) (173) to receive measurement results from thetransceiver(s) (123) and the motion sensors (121), and determine theposition of the mobile device (101) in a way as discussed above inconnection with FIG. 1.

The memory (167) may optionally store data such as the distribution ofradio frequency fingerprints in the indoor environment, the locations ofbeacons (103, 105), etc. Alternatively or in combination, the mobiledevice (101) communicates with a remote server to obtain such data(e.g., when such data is needed, or for storing in the memory (167)after the mobile device (101) enters the indoor environment asillustrated in FIG. 1).

Optionally, the beacons (103 and 105) broadcast not only theiridentities, but also related data, such as the location of the beacons(130 and 105), the expected travel speed of the corridor (109), etc.When such data is not included in the beacon signals, the mobile device(101) may look up such data from the memory (167) or query the remoteserver.

In the above discussion, the peak beacon signal strength is determinedby the mobile device (101) receiving the beacon signals from the beacons(103, 105). Alternatively, the mobile device (101) may transmit thebeacon signals to the corresponding beacons (103, 105), which areconnected to a centralized remote server to compute the location of themobile device (101). Similarly, the mobile device (101) may provide theradio frequency fingerprint measurements to the server for adetermination of the location of the mobile device (101). Thus, theposition calculations can be performed at least in part on the remoteserver.

FIG. 3 shows a method to determine a location of a mobile deviceaccording to one embodiment. The method of FIG. 3 can be implemented inthe system of FIG. 1 using a mobile device (101) illustrated in FIG. 2.

In FIG. 3, the mobile device (101) is configured to: provide (201) afirst beacon device at a first location of a transport corridor in amulti-floor environment; provide (203) a second beacon device at asecond location of the transport corridor; determine (205) the mobiledevice being in the vicinity of the first location at a first timeinstance based on a peak of beacon signal power received from the firstbeacon device; determine (207) the mobile device being in the vicinityof the second location at a second time instance based on a peak ofbeacon signal power received from the second beacon device; correlate(209) the movement of the mobile device from the first location to thesecond location with a predetermined traffic speed along the corridor;and determine a position and/or (211) a speed of the mobile device at atime instance based on the movement of the mobile device from the firstlocation to the second location along the corridor.

A method in the present disclosure includes: providing a first beacondevice (103) at a first location of a transport corridor in amulti-floor environment; and providing a second beacon device (105) at asecond location of the transport corridor (e.g., as illustrated in FIG.1). After a mobile device (101) is determined to be at the firstlocation at a first time instance based on a peak of beacon signal powerfrom the first beacon device and at the second location at a second timeinstance based on a peak of beacon signal power from the second beacondevice, the movement of the mobile device from the first location to thesecond location is correlated with a predetermined traffic speed alongthe corridor. The position and speed of the mobile device (101) at atime instance (e.g., between the first time instance and the second timeinstance) are determined based on the movement of the mobile device fromthe first location to the second location along the corridor, if themovement is consistent with predetermined traffic speed. Examples of thetransport corridor include: a stairway, an escalator, an elevator, and apathway or walkway having an entrance and an exit.

For example, based on the position and speed of the mobile device, aninitial position and an initial speed used in an inertial guidancesystem of the mobile device can be calibrated, where the mobile deviceuses motion sensors to measure acceleration and rotation of the mobiledevice to track a current location of the mobile device from the initialposition and the initial speed. For example, the position and speed ofthe mobile device determined from the movement of the mobile device inthe corridor can be used as the initial position and the initial speed.

For example, the position of the mobile device can be used to improve aposition determination result from a radio frequency fingerprint-basedlocation determination system of the mobile device, where the mobiledevice measures a radio frequency fingerprint and determines a locationof the mobile device based on correlation the radio frequencyfingerprint with a predetermined distribution of radio frequencyfingerprints in the multi-floor environment. For example, the positionof the mobile device determined from the movement of the mobile devicein the corridor can be used to select a floor from a plurality of floorsin the multi-floor environment (e.g., to limit the correlation to theparticular selected floor and/or prevent floor-jumping in thecorrelation).

Another method in the present disclosure includes: measuring, by amobile device (101), a radio frequency fingerprint; correlating theradio frequency fingerprint to a predetermined distribution of radiofrequency fingerprints in a multi-floor environment to determine a firstlocation determination result; measuring, by the mobile device (101),accelerations of the mobile device as a function of time; determining asecond location determination result based on the accelerations (e.g.,via a time integration of the accelerations); receiving, in the mobiledevice, a first beacon signal from a beacon device (103) disposed at afirst location of a transport corridor in the multi-floor environment;determining a first location of the beacon device (103) based on thefirst beacon signal; and computing a location of the mobile device (101)based on the first location of the beacon device, the first locationdetermination result, and the second location determination result.

For example, after receiving in the mobile device (101), a second beaconsignal from the beacon device, a second location of the beacon devicecan be determined based on the second beacon signal, where the locationof the mobile device can be computed further based on the secondlocation of the beacon device. For example, the beacon device may bedisposed on a transport corridor in the form of an escalator or anelevator, where the beacon device travels with the escalator or elevatorto transport the user who is carrying the mobile device (101). Forexample, a speed of the mobile device can be determined based on thefirst location and the second location of the beacon device; and thesecond location determination result can be determined based at least inpart on the speed of the mobile device and a time integration of theaccelerations. In some implementations, the first beacon signalidentifies the first location of the beacon device; and the secondbeacon signal identifies the second location of the beacon device. Inother implementations, the identifier(s) of the beacon(s) and/or thetimes of the beacon signals can be used to look up the beacon locationsfrom a remoter server. Further, the beacon location can be used toselect a floor in the first location determination result determinedfrom radio frequency fingerprint correlation.

In another example, the mobile device receives the second beacon signalfrom a second beacon device (105) to determine the second location.Then, a speed of the mobile device (101) can be based on the firstlocation of the first beacon device (103) and the second location of thesecond beacon device (105) that are located on different part of thetransport corridor, such as a stairway, a pathway or walkway having anentrance and an exit, an escalator, an elevator, etc. The speed can beused as a basis from which time integration of accelerations can be usedto track the subsequent locations of the mobile device (101) based onthe measurement of the motion sensors.

A further method of the present disclosure includes: measuring, using atleast one transceiver (123) of a mobile device (101), a radio frequencyfingerprint; determining a first location determination result based oncorrelating the radio frequency fingerprint to a predetermineddistribution of radio frequency fingerprints in a multi-floorenvironment; measuring, using a motion sensor (121) of the mobile device(101), accelerations of the mobile device as a function of time;determining a second location determination result based on theaccelerations; and computing a location of the mobile device bycombining the first location determination result and the secondlocation determination result.

For example, after estimating an accuracy of the first location resultand an accuracy of the second location result, the mobile device (101)(or a remote server in communication with the mobile device (101))combines the first location determination result and the second locationdetermination result based on the accuracy of the first location resultand the accuracy of the second location result. The combination of thefirst location determination result and the second locationdetermination result can be in the form of a weighted average of thefirst location determination result and the second locationdetermination result, where weights of first location determinationresult and the second location determination result are based on theaccuracy of the first location result and the accuracy of the secondlocation result.

Further, the mobile device (101) may optionally receive at least twobeacon signals from at least one beacon device (e.g., 103 and/or 105)disposed on a transport corridor in a multi-floor environment todetermine at least two beacon positions corresponding to the at leasttwo beacon signals. A position and a speed of the mobile device (101) onthe transport corridor are estimated based on the at least two beaconpositions and used in the computation of the location of the mobiledevice.

For example, the position and the speed of the mobile device (101) onthe transport corridor estimated based on the at least two beaconpositions can be used as an initial solution to time integrateaccelerations measured by the motion sensor and track the location ofthe mobile device. Further, the position the mobile device on thetransport corridor estimated based on the at least two beacon positionscan be used to identify a floor in a multi-floor environment and thuslimit the areas of correlation of radio frequency fingerprints.

The present disclosure includes a non-transitory computer storage mediumstoring instructions configured to instruct a computing apparatus toperform various methods discussed above and computing apparatuses havingat least: a motion sensor; at least one transceiver; at least onemicroprocessor; and a memory storing instructions configured to instructthe at least one microprocessor and the at least one transceiver toperform any of the methods.

The systems and methods discussed above use fewer beacons to bedeployed, relative to a solution not employing this method, to achievecontinuous, high-accuracy positioning results. Results of the systemsand method are generally more accurate than the results of a radiofrequency fingerprint-based location estimate or an inertial guidancelocation estimate.

Precise positioning (defined here as within 1-2 meters 90% of the time)has yet to be reliably achieved in the prior art. This level of accuracyconsistently allows for a vastly improved user experience whennavigating a large indoor space such as a shopping center. It allowsmore precise targeting of communications within the space. For example,assuming the consumer has opted in to receive such messages and/orpromotions, with this level of consistent positioning fidelity, aretailer could send a communication or promotion to a specific consumeras she walked by the storefront of the retailer. Such real-time,highly-contextual messaging and promotion is more valuable toadvertisers than is general or even “area-based” messaging.

Additionally, there is value for shopping center owners in understandingtraffic flows within their centers, in order to 1) promote leasingefforts, and, 2) better understand both individual and aggregate shopperbehavior (e.g., gaining a precise understanding of who goes where, andhow long they spend in each location and in transit) to bettermerchandise store mix within the center. The solution as describedshould allow the precision necessary to acquire positioning data with avery small margin of error, unlike many other solutions.

In at least some embodiments, a mobile device is configured to combinelocation determination results from radio frequency signals and motionsensor signals to improve location determination accuracy.

FIG. 5 shows a mobile device for its location determination according toone embodiment. Various methods discussed in the present application canbe implemented in a mobile device (101) illustrated in FIG. 5 (or FIG.1).

In FIG. 5, the mobile device (101) includes a global positioning system(GPS) receiver (301) configured to receive and process signals from GPSsatellites. Alternative satellite positioning systems and correspondingreceivers can also be used, such as Galileo positioning system ofEuropean Union, BeiDou Navigation Satellite System of China,Quasi-Zenith Satellite System of Japan, and Indian Regional NavigationSatellite System of India. Based on the satellite signals, the mobiledevice (101) computes the location of the mobile device (101) usingsatellite positioning techniques currently known in the field. Satellitepositioning techniques that may be developed in the future can also beused.

When the mobile device (101) is used in an indoor environment, the poorreception of satellite signals from satellite positioning systems mayprevent the satellite positioning system from producing locationdetermination results, or prevent the satellite positioning system fromproducing accurate location determination results for the mobile device(101).

In one embodiment, when the mobile device (101) detects that itslocation is approaching or entering a known indoor environment (e.g.,based on its current location on a map of known environments, or basedon the strength of the satellite positioning signals), the mobile device(101) turns off the operation of the receiver (301) (e.g., to reducepower consumption), and starts one or more mobile applications (125),executing in the microprocessor(s), that determine the location of themobile device (101) based on alternative signals, such as the signalsfrom the motion sensors (121) and/or the transceivers of radio frequencysignals, such as the signals for wireless local area networking (e.g.,WiFi signals), signals for wireless personal area networking (e.g.,Bluetooth signals), beacon signals, etc.

When the mobile device (101) is primarily designed for use in the indoorenvironment, the receiver (301) of a satellite positioning system can beomitted.

For example, the motion sensors (121) include accelerometers (311) thatmeasure the accelerations of the mobile device (101) in which theaccelerometers (311) are installed. The acceleration measurements as afunction of time can be integrated over a time period to determine thechange of the velocity of the mobile device (101), which can be furtherintegrated over the time period to determine the change of the positionof the mobile device (101).

In an inertial navigation system, motion sensors (121), such asaccelerometers (311) and gyroscopes (315), are used to continuouslycalculate via dead reckoning the position, orientation, and velocity(direction and speed of movement) of a moving object (e.g., the mobiledevice (101)), without using an external reference system. Through deadreckoning, a previously determined velocity, position, or orientation isupdated based on the acceleration, velocity, or spinning of the objectto arrive at the currently determined velocity, position, ororientation. Using the measurement data from the motion sensors (121),dead reckoning techniques currently known in the field can be used toupdate the velocity, position, or orientation of the mobile devices.Dead reckoning techniques that may be developed in the future can alsobe used.

The orientation of the mobile device (101) can also be determined basedon the measurement of magnetic field sensors (313) in reference to themagnetic field of the earth.

In FIG. 5, the mobile device (101) includes not only the inertialnavigation system that determines its position based on the measurementsof the motion sensors (121), but also a radio frequency navigationsystem that determines its position in reference to a map (317) of radiofrequency signals.

For example, the signal map (317) contains data indicating the radiofrequency signal strength of one or more radio frequency sourcespositioned within an area (e.g., an indoor environment, such as ashopping mall). Examples of the radio frequency sources include accesspoints (107 illustrated in FIG. 1), repeaters, and/or routers forwireless local area network, Bluetooth devices, beacon devices (103, 105illustrated in FIG. 1), etc. The radio frequency signals received in thetransceivers (123) include the identity information of the radiofrequency sources. After measuring the signal strengths of the radiofrequency signals from one or more sources, a mobile application (125)executed by the microprocessor(s) finds a matched location in the signalmap (317) that has radio frequency characteristics (e.g., sourceidentification information and signal strength) that agrees with themeasured data.

Thus, the radio frequency navigation system of the mobile device (101)the inertial navigation system of the mobile device (101), and/or theGPS receiver (301) can track the locations of the mobile device (101)substantially independent from each other.

In various methods disclosed in the present application, the confidencelevels of the position determination results produced by the differentposition determination systems of the mobile device (101) are evaluatedto combine the results. Further, the high confidence level results fromone system are used in another system to improve the overall accuracy ofthe position determination results from the mobile device (101).

For example, the radio frequency navigation system can produce accuracyresults at certain locations but inaccurate results at other locations.The inertial navigation system can produce accurate results within ashort time period after an accurate initialization of the initialposition and velocity, but inaccuracy accumulates over a long period oftime to cause a drift away from accurate results. Thus, when the radiofrequency navigation system produces an accurate result, the mobileapplication(s) (125) can be configured to automatically re-initializethe inertial navigation system using the result from the radio frequencynavigation system. Further, the capability of the inertial navigationsystem in dead reckoning the position of the mobile device (101) for ashort period of time allows the mobile application(s) (125) to generatea local distribution of radio frequency signals for improved matchingwith the signal map (317) in position determination. The positiondetermination results of the radio frequency navigation system can befiltered based on a minimum distance threshold to remove inaccurateposition changes (e.g., caused by fluctuation in radio frequencymeasurements and environment) and/or a maximum distance threshold toremove inaccurate position determination results (e.g., caused by themap (317) containing multiple locations that have similar radiofrequency signal characteristics). Further, the pattern of the locationsdetermined by the radio frequency navigation system can be examined forindication of inaccuracy. For example, when the determined locations arewithin a circle having a radius less than a threshold, the mobile device(101) is considered in a “dwelling” state; and the locationdetermination results from the radio frequency navigation system is thennot used to update the location of the mobile device. For example, whenthe determined locations from the radio frequency navigation system jumpfrom one floor to another floor near the same horizontal location, theradio frequency navigation system produces an inaccurate altitude result(e.g., due to the similarity between the radio frequency signals betweenthe two floors). When the confidence levels of the results of the radiofrequency navigation system and the radio frequency navigation systemare both within a predetermined range, the results can be combined viaan average process weighted according to the confidence levels to updatethe position of the mobile device (101) (e.g., the higher the confidencelevel, the heavier the weight in the weighted average process).

FIG. 6 shows a method to improve an inertial position determinationsystem based on a radio frequency position determination systemaccording to one embodiment. For example, the method of FIG. 6 can beimplemented in the mobile device (101) illustrated in FIG. 2 or 5.

In FIG. 6, the mobile device (101) is configured to use the locationdetermination results from its radio frequency navigation system tore-initiate its inertial navigation system when the radio frequencynavigation system produces more accurate results than the inertialnavigation system.

The radio frequency navigation system of the mobile device (101) receive(331) radio frequency signals from a transceiver (123) of the mobiledevice (101) and determines (333) characteristics of the radio frequencysignals. The mobile device (101) compares (335) the determinedcharacteristics to a map (317) of radio frequency signal characteristicsof a region to determine (337) a location of the mobile device in theregion, based on matching the determined characteristics to thecharacteristics in the map.

After the mobile device (101) determines (341) an initial estimate ofthe location of the mobile device (e.g., based on a positiondetermination result from the GPS receiver (301), the radio frequencynavigation system), the inertial navigation system of the mobile device(101) receives (343) inputs from inertial sensors (e.g., accelerometers(311), gyroscopes (315)) of the mobile device (101) and integrates (345)the inertial sensor inputs over a period of time to determine an updateto the initial estimate of the location of the mobile device (101).Based on the initial estimate of the location of the mobile device andthe location update determined from the inertial sensor inputs, themobile device (101) computes (347) (e.g., using a mobile application(125)) an updated location of the mobile device.

The mobile device (101) determines (339) a confidence level of thelocation determined based on the received radio frequency signals fromthe signal map (317), and determines (349) a confidence level of thelocation updated according to the inertial sensor inputs.

For example, the confidence level of the location determined by theradio frequency navigation system of the mobile device (101) depends onthe uniqueness level of the determined characteristics of the radiofrequency signals in the map (317); and the accuracy of the locationdetermined by the radio frequency navigation system of the mobile device(101) depends on the degree of variation of the characteristics in thevicinity of the determined locations in the map (317) (e.g., the largerthe variation, the more accurate is the determined result).

For example, the confidence level of the location determined by theinertial navigation system of the mobile device (101) depends on theaccuracy of the initial estimate and the length of the period of time.The longer the length of the time period in which the user is moving,the greater is the drift in the result from the inertial navigationsystem.

The mobile device (101) selects (351), as the location of the mobiledevice (101) one of: the location determined from the radio frequencysignals by the radio frequency navigation system, and the locationdetermined from the inertial inputs by the inertial navigation system.The location result that has a higher confidence level is selected asthe location of the mobile device (101).

In FIG. 6, the selected location result that has a higher confidencelevel is used (341) as the initial estimate in dead reckoning operationsin the inertial navigation system.

Thus, the method as illustrated in FIG. 6 uses the result of the radiofrequency navigation system to re-initialize the inertial navigationsystem, whenever the radio frequency navigation system produces superiorresults (e.g., at or near locations where the radio frequency navigationsystem can provide accurate results). When the radio frequencynavigation system fails to produce superior results relative to theinertial navigation system, the inertial navigation system provideslocation determination results (e.g., in regions where the radiofrequency navigation system is not able to provide accurate results).

Alternatively, the results of the radio frequency navigation system canbe used to periodically re-initiate the inertial navigation system(e.g., at a predetermined time interval, or when the confidence level ofthe result of the inertial navigation system is below a threshold).

The location determination results of the inertial navigation system canoptionally be used to improve the location determination operations ofthe radio frequency navigation system, as illustrated in FIG. 7.

FIG. 7 shows a method to combine an inertial position determinationsystem and a radio frequency position determination system according toone embodiment. For example, the method of FIG. 7 can be implemented inthe mobile device (101) illustrated in FIG. 2 or 5.

In FIG. 7, the inertial position determination system of the mobiledevice (101) is configured to identify a set of recent locations of themobile device (101) relative to each other. Since the set of locationsare determined to be relative to each other, the accuracy of thedetermination results is independent from the initial estimate and thelength of the lapsed time since the initial estimate. The radiofrequency characteristics determined for the set of recent locationsform a local distribution of the radio frequency characteristics. Bymapping the local distribution to a region in the signal map (317), theradio frequency navigation system can improve its location determinationresult.

For example, after the mobile device (101) determines (371) an initialestimate of the location of the mobile device (101) and receives (373)input from inertial sensors (e.g., motion sensors (121)) of the mobiledevice (101) over a period of time, the mobile device (101) determines(375) (e.g., using a mobile application (125)) a plurality of locationsof the mobile device (101) over the period of time, based on the inputsfrom the inertial sensors (e.g., motion sensors (121)). The plurality oflocations determined by the inertial navigation system is provided tothe radio frequency navigation system of the mobile device to form alocal distribution of radio frequency signal characteristics.

For example, after radio frequency signals are received (361) from atransceiver (123) of the mobile device (101) over the period of time,the mobile device (101) determines (363) (e.g., using a mobileapplication (125)) the characteristics of the radio frequency signalsover the period of time. By correlating the time of the determinedcharacteristics and the plurality of locations determined by theinertial navigation system, the mobile device (101) determines (365) alocal distribution of the characteristics over the plurality oflocations. Based on matching the local distribution to a portion ofcharacteristics in the map (319), the radio frequency navigation systemdetermines (367) a current location of the mobile device in the map(319).

The location determined from mapping the local distribution to a map istypically more accurate than the location determined from mapping theradio frequency characteristics at the current location to the map.

The result of the radio frequency navigation system can be used tore-initialize the inertial navigation system, in a way similar to thatdiscussed in connection with FIG. 6.

For example, after the mobile device (101) determines (377) a confidencelevel of the current location determined from the inertial sensor inputand determines (369) a confidence level of the current locationdetermined from the map and the local distribution, the mobile deviceselects (379) one of the determined current locations that has a higherconfidence level (379). The selected location result can be used tore-initialize (371) the inertial navigation system.

Alternatively, re-initialization of the inertial navigation system canbe performed periodically and/or when the confidence level of thelocation results from the inertial navigation system is below athreshold.

The locations used in the determination of the local distribution of theradio frequency signals can be updated on a continuous basis as morelocations are determined from the inertial navigation system; and theupdated set of locations for the local region can be used as the basisto construct the updated local distribution for mapping with a portionin the signal map (317).

For example, a predetermined number of locations last determined fromthe inertial navigation system can be used for the local region for theconstruction of a measured local distribution, as illustrated in FIG. 8.

FIG. 8 shows a method to improve a radio frequency positiondetermination system based on an inertial position determination systemaccording to one embodiment. For example, the method of FIG. 8 can beimplemented in the mobile device (101) illustrated in FIG. 2 or 5.

In FIG. 8, the inertial navigation system of the mobile devicedetermines (381) a plurality of locations over a period of time based oninertial sensor inputs. After receiving (383) additional inputs frominertial sensors (e.g., motion sensors (121)) of the mobile device(101), the inertial navigation system of the mobile device determines anadditional location of the mobile device following the period of time,based on the additional inputs from the inertial sensors (e.g., motionsensors (121)). The mobile device (101) selects (387) a predeterminednumber of last locations and determines (389) a local distribution ofmeasured radio frequency characteristics at the predetermined number oflast locations. The radio frequency navigation system then determines(391) a current location of the mobile device (101) in a signal map(317) based on matching the local distribution to a portion of thesignal map (317).

When further additional inputs are received (383), a further additionallocation is determined (385) by the inertial navigation system, whichleads to an update for the last locations selected (387) for thedetermination (389) of the local distribution. The updated localdistribution is used by the radio frequency navigation system todetermine (391) the updated current location of the mobile device (101).

When the current location of the mobile device (101) determined by theradio frequency navigation system is determined to have a highconfidence level, the current location of the mobile device (101) can beused to re-initialize the inertial navigation system, in a way similarto those discussed in connection with FIG. 6 or FIG. 7.

In one embodiment, when the current location of the mobile device (101)determined by the radio frequency navigation system is used tore-initialize the inertial navigation system, the mobile device (101)uses the difference between the current location of the mobile device(101) determined by the radio frequency navigation system and thecurrent location of the mobile device (101) determined by the inertialnavigation system to correct the set of predetermined locations used forthe local distribution, such that when an additional location determinedby the re-initialized inertial navigation system is obtained (383, 385),an additional location can be used with the corrected set of locationsto form an updated local distribution.

For example, locations l1, l2, . . . , ln determined for time instancest1, t2, . . . , tn can be used to form a local distribution of signalstrength s1, s2, . . . , sn over the locations l1, l2, . . . , ln formatching with the signal map (317). When the matching provides anaccurate result of location Ln for the mobile device (101), the mobiledevice (101) determines the correction of Ln−ln for the location resultsdetermined by the inertial navigation system. The correction is added tothe locations at time instances t1, t2, . . . , tn to generate correctedlocations l1+Ln−ln, l2+Ln−ln, . . . , Ln. When the re-initializedinertial navigation system computes location lm for the next timeinstance tm, where m=n+1, the local distribution of signal strength s2,. . . , sn, sm over the locations l2+Ln −ln, . . . , Ln, lm can be usedfor matching with the signal map (317) to update the current location ofthe mobile device.

In some instances, when the results of the radio frequency navigationsystem are determined to have a confidence level lower than a threshold,the results can be discarded in favor of the results from the inertialnavigation system, as illustrated FIGS. 9-11.

FIG. 9 shows a method to combine the location determination results froman inertial position determination system and a radio frequency positiondetermination system according to one embodiment. For example, themethod of FIG. 8 can be implemented in the mobile device (101)illustrated in FIG. 2 or 5.

In FIG. 9, the radio frequency navigation system of the mobile device(101) determines (401) a current location of a mobile device (101) basedon a signal map (317) of radio frequency signal characteristics. Forexample, the current location can be determined by the radio frequencynavigation system without the use of location data from the inertialnavigation system, as discussed in connection with FIG. 6, or determinedwith the location data from the inertial navigation system to constructa local distribution as discussed in connection with FIGS. 7 and 8.

In FIG. 9, the inertial navigation system of the mobile device (101)determines (409) a current location of the mobile device (101) based oninputs from inertial sensors (e.g., motion sensors (121)).

In FIG. 9, when the confidence level of the current location of themobile device (101) determined by the radio frequency navigation systemis below (403) a first threshold, the current location determinationresult determined by the radio frequency navigation system is discarded.

In FIG. 9, when the confidence level of the current location of themobile device (101) determined by the radio frequency navigation systemis above (405) a second threshold, the current location determinationresult determined by the radio frequency navigation system is used toinitialize (407) inertial based location calculation. Thus, the inertialnavigation system of the mobile device (101) is re-initialized orcalibrated using the result of the radio frequency navigation system.

In FIG. 9, when the confidence level of the current location of themobile device (101) determined by the radio frequency navigation systemis between (403, 405) the first threshold and the second threshold, themobile device (101) determines (411) a current location of the mobiledevice based on a weighted average of the current location determinedfrom the map and the current location determined from the inertialsensor inputs.

The mobile device (101) may or may not use the current location of themobile device determined from the weighted average to reinitialize theinertial navigation system.

In some instances, the second threshold is the confidence level of thelocation determination result of the inertial navigation system.

FIG. 10 shows a method to filter the location determination results froma radio frequency position determination system based on a minimumdistance according to one embodiment. For example, the filtering can beperformed in connection with the first threshold of FIG. 9 andimplemented in the mobile device (101) illustrated in FIG. 2 or 5.

In FIG. 10, using the radio frequency signals received (421) from atransceiver (123) of a mobile device (101) over a period of time, theradio frequency navigation system of the mobile device (101) determines(423) characteristics of the radio frequency signal over the period oftime and determines (425) a plurality of locations of the mobile deviceduring the period of time, based on matching the characteristics of theradio frequency signals to a map (317) of characteristics of radiofrequency signals.

If the mobile device (101) determines (427) that these locations,determined by the radio frequency navigation system, are within aminimum distance threshold from each other, the mobile device (101)assigns (429) a confidence level below a threshold (e.g., the firstthreshold in FIG. 9) to the current location of the mobile device (101)computed from the radio frequency signals; otherwise, the mobile device(101) determines (431) a confidence level of a current location of themobile device computed from the radio frequency signals based on otherconsiderations (e.g., the gradient of the characteristics of radiofrequency signals at the determined location, the presence of similarcharacteristics of radio frequency signals at different locations in themap, a maximum threshold distance discussed below).

In one embodiment, when the successive locations of the mobile device(101) during a period of time as determined from the signal map (317)are within a circle of a predetermined radius, or within a minimumdistance from each other, the mobile device (101) computes an average ofthe successive locations and uses the average to represent the locationof the mobile device within the period of time.

FIG. 11 shows a method to filter the location determination results froma radio frequency position determination system based on a maximumdistance according to one embodiment. For example, the filtering can beperformed in connection with the first threshold of FIG. 9 andimplemented in the mobile device (101) illustrated in FIG. 2 or 5. Thefiltering methods of FIGS. 10 and 11 can be used together.Alternatively, one of the filtering methods of FIGS. 10 and 11 is usedwithout another.

In FIG. 11, the mobile device (101) receives (441) radio frequencysignals from a transceiver (123) over a period of time to determine(443) characteristics of the radio frequency signal over the period oftime. The radio frequency navigation system of the mobile device (101)determines (445) a plurality of locations of the mobile device duringthe period of time, based on matching the characteristics of the radiofrequency signals to a map (317) of characteristics of radio frequencysignals.

If the mobile device (101) determines (447) that these locations,determined by the radio frequency navigation system, are separated bymore than a maximum distance threshold, the mobile device (101) assigns(449) a confidence level below a threshold (e.g., the first threshold inFIG. 9) to the current location of the mobile device computed from theradio frequency signals; otherwise, the mobile device determines (451) aconfidence level of a current location of the mobile device computedfrom the radio frequency signals based on other considerations (e.g.,the gradient of the characteristics of radio frequency signals at thedetermined location, the presence of similar characteristics of radiofrequency signals at different locations in the map, a minimum thresholddistance discussed above).

In one embodiment, the maximum distance threshold is more than a typicaldistance traveled by the user of the mobile device during the period oftime in an indoor environment (e.g., illustrated in FIG. 1). Forexample, the mobile device (101) (or a separate server) tracks thehistoric speeds of the user traveling within the indoor environment andcomputes an average speed of the user from the tracked speeds. Themaximum threshold distance can be computed for the period of time basedon the average speed (e.g., a predetermined number of times of thedistance traveled during the period of time at the average speed).Alternatively, a maximum observed speed can be computed from the trackedspeed to compute the maximum threshold distance. In some instances, themaximum threshold distance can be computed based on a typical walkingspeed of an adult. In other instances, the maximum threshold distancecan be computed based on the current speed of the mobile device asdetermined by the inertial navigation system.

In some embodiments, the inertial navigation system uses themeasurements from the magnetic field sensor (313) and/or the gyroscopes(315) to determine the orientation of the mobile device (101) andcombines the orientation of the mobile device (101) with themeasurements from the accelerometers (311) to incrementally update thelocation of the mobile device over a period of time.

However, the mobile device (101) may or may not have a fixed orientationwith respect to the user of the mobile device (101). Thus, the headingof the mobile device (101) may not accurately reflect the heading of theuser. The heading of the user can be used to predict the next locationof the user and evaluate the confidence level of a subsequently computedlocation (e.g., from the inertial navigation system and/or the radiofrequency navigation system). In one embodiment, the mobile device (101)ignores the heading data of the mobile device and computes the headingfrom the vectors defined by the successive locations of the mobiledevice (101), as illustrated in FIG. 12.

FIG. 12 shows a method to determine the heading of a person carrying amobile device according to one embodiment. For example, the method ofFIG. 12 can be implemented in the mobile device (101) illustrated inFIG. 2 or 5.

In FIG. 12, the radio frequency navigation system of the mobile device(101) receives (461) radio frequency signals from a transceiver (123)over a period of time to determine (463) characteristics of the radiofrequency signals over the period of time and determine (465) locationsof the mobile device based on matching the determined characteristics toa map of radio frequency signal characteristics.

In FIG. 12, the inertial navigation system of the mobile device (101)receives (471) input from sensors of the mobile device over the periodof time to compute (475) locations of the mobile device from the sensordata. The mobile device discards (473) orientation data from the sensorsand combines (467) the locations determined from the map and thelocations determined from the sensor data to generate successivelocations. The combination of location data can be performed using oneor more of the techniques discussed in connection with FIGS. 6-9.

The mobile device computes (469) headings of a person carrying themobile device from the successive locations. The computed heading of theuser can be used to predict the next location of the user and evaluatethe confidence level of a subsequently computed location (e.g., from theinertial navigation system and/or the radio frequency navigationsystem).

FIG. 4 illustrates a data processing system according to one embodiment.For example, the data processing system of FIG. 4 can be used toimplement each of the mobile device (101), the beacons (103, 105), theWi-Fi Access Point (107), and/or a centralized remote service discussedabove.

While FIG. 4 illustrates various components of a computer system, it isnot intended to represent any particular architecture or manner ofinterconnecting the components. One embodiment may use other systemsthat have fewer or more components than those shown in FIG. 4.

In FIG. 4, the data processing system (170) includes an inter-connect(171) (e.g., bus and system core logic), which interconnects amicroprocessor(s) (173) and memory (167). The microprocessor (173) iscoupled to cache memory (179) in the example of FIG. 4.

In one embodiment, the inter-connect (171) interconnects themicroprocessor(s) (173) and the memory (167) together and alsointerconnects them to input/output (I/O) device(s) (175) via I/Ocontroller(s) (177). I/O devices (175) may include a display deviceand/or peripheral devices, such as mice, keyboards, modems, networkinterfaces, printers, scanners, video cameras and other devices known inthe art. In one embodiment, when the data processing system is a serversystem, some of the I/O devices (175), such as printers, scanners, mice,and/or keyboards, are optional.

In one embodiment, the inter-connect (171) includes one or more busesconnected to one another through various bridges, controllers and/oradapters. In one embodiment the I/O controllers (177) include a USB(Universal Serial Bus) adapter for controlling USB peripherals, and/oran IEEE-1394 bus adapter for controlling IEEE-1394 peripherals.

In one embodiment, the memory (167) includes one or more of: ROM (ReadOnly Memory), volatile RAM (Random Access Memory), and non-volatilememory, such as hard drive, flash memory, etc.

Volatile RAM is typically implemented as dynamic RAM (DRAM) whichrequires power continually in order to refresh or maintain the data inthe memory. Non-volatile memory is typically a magnetic hard drive, amagnetic optical drive, an optical drive (e.g., a DVD RAM), or othertype of memory system which maintains data even after power is removedfrom the system. The non-volatile memory may also be a random accessmemory.

The non-volatile memory can be a local device coupled directly to therest of the components in the data processing system. A non-volatilememory that is remote from the system, such as a network storage devicecoupled to the data processing system through a network interface suchas a modem or Ethernet interface, can also be used.

In this description, some functions and operations are described asbeing performed by or caused by software code to simplify description.However, such expressions are also used to specify that the functionsresult from execution of the code/instructions by a processor, such as amicroprocessor.

Alternatively, or in combination, the functions and operations asdescribed here can be implemented using special purpose circuitry, withor without software instructions, such as using Application-SpecificIntegrated Circuit (ASIC) or Field-Programmable Gate Array (FPGA).Embodiments can be implemented using hardwired circuitry withoutsoftware instructions, or in combination with software instructions.Thus, the techniques are limited neither to any specific combination ofhardware circuitry and software, nor to any particular source for theinstructions executed by the data processing system.

While one embodiment can be implemented in fully functioning computersand computer systems, various embodiments are capable of beingdistributed as a computing product in a variety of forms and are capableof being applied regardless of the particular type of machine orcomputer-readable media used to actually effect the distribution.

At least some aspects disclosed can be embodied, at least in part, insoftware. That is, the techniques may be carried out in a computersystem or other data processing system in response to its processor,such as a microprocessor, executing sequences of instructions containedin a memory, such as ROM, volatile RAM, non-volatile memory, cache or aremote storage device.

Routines executed to implement the embodiments may be implemented aspart of an operating system or a specific application, component,program, object, module or sequence of instructions referred to as“computer programs.” The computer programs typically include one or moreinstructions set at various times in various memory and storage devicesin a computer, and that, when read and executed by one or moreprocessors in a computer, cause the computer to perform operationsnecessary to execute elements involving the various aspects.

A machine readable medium can be used to store software and data whichwhen executed by a data processing system causes the system to performvarious methods. The executable software and data may be stored invarious places including for example ROM, volatile RAM, non-volatilememory and/or cache. Portions of this software and/or data may be storedin any one of these storage devices. Further, the data and instructionscan be obtained from centralized servers or peer to peer networks.Different portions of the data and instructions can be obtained fromdifferent centralized servers and/or peer to peer networks at differenttimes and in different communication sessions or in a same communicationsession. The data and instructions can be obtained in entirety prior tothe execution of the applications. Alternatively, portions of the dataand instructions can be obtained dynamically, just in time, when neededfor execution. Thus, it is not required that the data and instructionsbe on a machine readable medium in entirety at a particular instance oftime.

Examples of computer-readable media include but are not limited torecordable and non-recordable type media such as volatile andnon-volatile memory devices, read only memory (ROM), random accessmemory (RAM), flash memory devices, floppy and other removable disks,magnetic disk storage media, optical storage media (e.g., Compact DiskRead-Only Memory (CD ROMS), Digital Versatile Disks (DVDs), etc.), amongothers. The computer-readable media may store the instructions.

The instructions may also be embodied in digital and analogcommunication links for electrical, optical, acoustical or other formsof propagated signals, such as carrier waves, infrared signals, digitalsignals, etc. However, propagated signals, such as carrier waves,infrared signals, digital signals, etc. are not tangible machinereadable medium and are not configured to store instructions.

In general, a machine readable medium includes any mechanism thatprovides (i.e., stores and/or transmits) information in a formaccessible by a machine (e.g., a computer, network device, personaldigital assistant, manufacturing tool, any device with a set of one ormore processors, etc.).

In various embodiments, hardwired circuitry may be used in combinationwith software instructions to implement the techniques. Thus, thetechniques are neither limited to any specific combination of hardwarecircuitry and software nor to any particular source for the instructionsexecuted by the data processing system.

The description and drawings are illustrative and are not to beconstrued as limiting. The present disclosure is illustrative ofinventive features to enable a person skilled in the art to make and usethe techniques. Various features, as described herein, should be used incompliance with all current and future rules, laws and regulationsrelated to privacy, security, permission, consent, authorization, andothers. Numerous specific details are described to provide a thoroughunderstanding. However, in certain instances, well known or conventionaldetails are not described in order to avoid obscuring the description.References to one or an embodiment in the present disclosure are notnecessarily references to the same embodiment; and, such references meanat least one.

The use of headings herein is merely provided for ease of reference, andshall not be interpreted in any way to limit this disclosure or thefollowing claims.

Reference to “one embodiment” or “an embodiment” means that a particularfeature, structure, or characteristic described in connection with theembodiment is included in at least one embodiment of the disclosure. Theappearances of the phrase “in one embodiment” in various places in thespecification are not necessarily all referring to the same embodiment,and are not necessarily all referring to separate or alternativeembodiments mutually exclusive of other embodiments. Moreover, variousfeatures are described which may be exhibited by one embodiment and notby others. Similarly, various requirements are described which may berequirements for one embodiment but not other embodiments. Unlessexcluded by explicit description and/or apparent incompatibility, anycombination of various features described in this description is alsoincluded here. For example, the features described above in connectionwith “in one embodiment” or “in some embodiments” can be all optionallyincluded in one implementation, except where the dependency of certainfeatures on other features, as apparent from the description, may limitthe options of excluding selected features from the implementation, andincompatibility of certain features with other features, as apparentfrom the description, may limit the options of including selectedfeatures together in the implementation.

The disclosures of the above discussed patent documents are herebyincorporated herein by reference.

In the foregoing specification, the disclosure has been described withreference to specific exemplary embodiments thereof. It will be evidentthat various modifications may be made thereto without departing fromthe broader spirit and scope as set forth in the following claims. Thespecification and drawings are, accordingly, to be regarded in anillustrative sense rather than a restrictive sense.

1. A method to determine a location of a mobile device, the methodcomprising: storing, in the mobile device, a map of radio frequencysignal characteristics in a region identified in the map; receiving, ina transceiver of the mobile device, radio frequency signals in theregion emitted from a plurality of beacons located in a transportcorridor within the region; determining, by the mobile device,characteristics of the radio frequency signals received in thetransceiver; matching, by the mobile device, the characteristics of theradio frequency signals with the frequency signal characteristics of themap to determine two successive first locations; generating, by sensorsof the mobile device, motion data, including orientation data andacceleration data of the mobile device; computing, by the mobile device,two successive second locations from the motion data; determining aconfidence level of the two successive first locations and a confidencelevel of the two successive second locations; determining, by the mobiledevice, two successive third locations of the mobile device, thedetermining being based at least on computed weighted averages of thetwo successive first locations and the two successive second locations,the computed weighted averages being based on the confidence levels ofthe two successive first locations and the two successive secondlocations; and computing, by the mobile device, a heading of a user ofthe mobile device based on the two successive third locations of themobile device.
 2. The method of claim 1, wherein the orientation data isignored during the computing of the heading of the user.
 3. The methodof claim 2, wherein the orientation data includes measurements from amagnetic field sensor.
 4. The method of claim 2, wherein the orientationdata includes measurements from gyroscopes.
 5. The method of claim 1,wherein the mobile device performs dead reckoning positions of themobile device based on the acceleration data.
 6. The method of claim 5,wherein the sensors includes accelerometers to generate the accelerationdata.
 7. (canceled)
 8. (canceled)
 9. The method of claim 1, wherein thecharacteristics of the radio frequency signals received in thetransceiver include an identifier of a source located within an indoorenvironment that transmits the radio frequency signals.
 10. The methodof claim 9, wherein the characteristics of the radio frequency signalsreceived in the transceiver include strength level indicators of theradio frequency signals transmitted from the source.
 11. Anon-transitory computer storage medium storing instructions which whenexecuted on a mobile device, cause the mobile device to perform a methodin determining a location of the mobile device, the method comprising:storing, in the mobile device, a map of radio frequency signalcharacteristics in a region identified in the map; receiving, in atransceiver of the mobile device, radio frequency signals in the regionemitted from a plurality of beacons located in a transport corridorwithin the region; determining, by the mobile device, characteristics ofthe radio frequency signals received in the transceiver; matching, bythe mobile device, the characteristics of the radio frequency signalswith the frequency signal characteristics of the map to determine twosuccessive first locations; generating, by sensors of the mobile device,motion data, including orientation data and acceleration data of themobile device; computing, by the mobile device, two successive secondlocations from the motion data; determining a confidence level of thetwo successive first locations and a confidence level of the twosuccessive second locations; determining, by the mobile device, twosuccessive third locations of the mobile device, the determining beingbased at least on computed weighted averages of the two successive firstlocations and the two successive second locations, the computed weightedaverages being based on the confidence levels of the two successivefirst locations and the two successive second locations; and computing,by the mobile device, a heading of a user of the mobile device based onthe two successive third locations of the mobile device.
 12. A mobiledevice, comprising: a memory; at least one microprocessor; a radiofrequency navigation system, having: a map, stored in the memory, ofradio frequency signal characteristics in a region identified in themap; a transceiver to receive, during a period of time, radio frequencysignals in the region emitted from a plurality of beacons located in atransport corridor within the region; and instructions stored in thememory and configured to instruct the at least one microprocessor todetermine locations of the mobile device based on matchingcharacteristics of the received radio frequency signals to the map; andan inertial navigation system, having: sensors to generate motion data,including orientation data and acceleration data of the mobile device;and instructions stored in the memory and configured to instruct the atleast one microprocessor to determine locations of the mobile devicethrough dead reckoning operations performed according to the motiondata; wherein the mobile device is configured to determine twosuccessive locations of the mobile device based at least on computedweighted averages of position determination results of the radiofrequency navigation system and position determination results of theinertial navigation system, the computed weighted averages being basedon a confidence level of the position determination results of the radiofrequency navigation system, and a confidence level of the positiondetermination results of the inertial navigation system, and wherein themobile device is further configured to compute a heading of a user ofthe mobile device based on the two successive locations of the mobiledevice.
 13. The mobile device of claim 12, wherein the mobile deviceignores an orientation of the mobile device in computing the headingfrom the two successive locations.
 14. The mobile device of claim 12,wherein the sensors include accelerometers to generate the accelerationdata.
 15. The mobile device of claim 14, wherein the sensors furtherincludes at least one of: gyroscopes and a magnetic field sensor. 16.The mobile device of claim 15, wherein the mobile device ignores theorientation data from the magnetic field sensor in determining theheading of the user.
 17. The mobile device of claim 12, wherein thecharacteristics of the radio frequency signals received in thetransceiver include: an identifier of a source that transmits the radiofrequency signals; and a signal strength level of the radio frequencysignals transmitted from the source.
 18. The mobile device of claim 12,wherein the radio frequency signals are signals for wireless local areanetworking or wireless personal area networking.
 19. (canceled)
 20. Themobile device of claim 13, wherein the mobile device is configured tofilter position determination results of the radio frequency navigationsystem based on the confidence level of the position determinationresults of the radio frequency navigation system.